A system for creating authenticating a user from user information, hardware profile, and combinations thereof, where the hardware profile includes user generated data stored on an electronic device.
Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A system for allowing an authorized transaction, comprising one or more processors, and one or more memory, wherein the one or more memories have stored thereon machine readable instructions that when executed by the one or more processors is configured to perform the functions of: receive user information about a user of a device; receive a device personality, the device personality comprising user generated data stored on the device; combine the user information and the device personality as a combined electronic identification; store the combined electronic identification on an authentication server; prior to the transaction, receive an updated user information and an updated device personality comprising user generated data stored on the device; compare an updated combined electronic identification from the updated user information and the updated device personality against the combined electronic identification; generate a confidence score using the updated combined electronic identification and the combined electronic identification; and allow the transaction to proceed when the confidence score is within a first set tolerance; wherein the first set tolerance is based on: collecting multiple user device personalities, creating statistical distributions to create statistical probabilities to determine how much an individual device personality associated with one user differs from another individual device personality associate with another user, and using the statistical probabilities to determine the set tolerance where a device to which a user has been assigned is statistically different form an other device from another user.
2. A method comprising the steps of: obtaining a device personality, the device personality comprising user generated data stored on the device; obtaining user information about a user of a device; authenticating the user from the user information, wherein authentication is positive when the user information meets an accepted tolerance; prior to the transaction and after authenticating the user, receiving an updated device personality comprising updated user generated data stored on the device; comparing the updated device personality against the device personality; and allowing the transaction to proceed only after comparing the device personality and the updated device personality and when the device personality and the updated device personality match within a set tolerance, wherein the set tolerance between the device personality and the updated device personality is determined by: collecting multiple user device personalities, creating statistical distributions to create statistical probabilities to determine how much an individual device personality associated with one user differs from another individual device personality associated with another user, and using the statistical probabilities to determine the second set tolerance where a device to which a user has been assigned is statistically different from an other device from another user.
This invention relates to a method for securely authenticating a user and authorizing a transaction based on device personality analysis. The method addresses the problem of ensuring that a user is authenticated and that the device being used has not been tampered with or altered in a way that could compromise security. The method involves obtaining a device personality, which consists of user-generated data stored on the device, and user information about the device user. The user is authenticated by verifying that the user information meets an accepted tolerance level. After authentication, the method receives an updated device personality, which includes updated user-generated data stored on the device. The updated device personality is compared against the original device personality. The transaction is only allowed to proceed if the device personality and the updated device personality match within a set tolerance. The set tolerance is determined by collecting multiple user device personalities, creating statistical distributions to analyze how much an individual device personality differs from another user's device personality, and using these statistical probabilities to establish a tolerance threshold. This ensures that the device being used is statistically different from devices associated with other users, enhancing security by detecting unauthorized device changes.
3. The method of claim 2 , wherein the comparing the device personality and the updated device personality comprises determining a percent difference between the device personality and the updated device personality.
A system and method for monitoring and analyzing device behavior involves tracking a device's personality, which represents its operational characteristics, and comparing it to an updated device personality to detect deviations. The device personality is derived from a set of operational parameters, such as performance metrics, usage patterns, or security attributes, collected over time. The system periodically updates the device personality based on new data to reflect current behavior. To assess changes, the system calculates a percent difference between the original device personality and the updated version. This comparison helps identify significant deviations that may indicate anomalies, performance issues, or security threats. By quantifying the difference, the system can trigger alerts or automated responses when the percent difference exceeds a predefined threshold. This approach enables proactive monitoring and maintenance of devices, ensuring consistent performance and security. The method is applicable to various devices, including computing systems, network equipment, and IoT devices, where behavioral consistency is critical. The percent difference calculation provides a standardized metric for evaluating changes, allowing for scalable and automated analysis across multiple devices.
4. The method of claim 3 , wherein allowing the transaction to proceed occurs when a percentage difference between the device personality and the updated device personality is between 0.02% and 76%.
A system and method for securely processing transactions involving device authentication compares a device personality, which is a unique identifier or characteristic of a device, with an updated device personality to determine whether a transaction should proceed. The device personality may include hardware or software attributes, cryptographic keys, or other unique identifiers that define the device's identity. The updated device personality is obtained through a verification process, such as a challenge-response protocol or a secure communication channel, to ensure its authenticity. The system calculates a percentage difference between the original device personality and the updated device personality. If the percentage difference falls within a predefined range of 0.02% to 76%, the transaction is allowed to proceed, indicating that the device is authenticated and trusted. This range accounts for minor variations that may occur due to normal device updates or environmental factors while preventing unauthorized devices from being accepted. The method ensures secure transaction processing by dynamically adjusting the acceptance criteria based on the degree of similarity between the device personalities.
5. A system for allowing an authorized transaction, comprising one or more processors, one or more memories, an input interface, and a transmitter, wherein the one or more memories have stored thereon machine readable instructions that when executed by the one or more processors is configured to perform the functions of: receive user information about a user; send data related to the user information to a server; send a device personality, from a device to the server, the device personality relating to user generated data stored on the device including user contacts, song names, photo names, pixel color of a background screen, or combinations thereof; send data related to an updated device personality comprising updated user generated data stored on the device to the server; compare the updated device personality against the device personality; allow the transaction to proceed only after comparing the device personality and the updated device personality and when the device personality and the updated device personality match within a set tolerance, wherein the set tolerance between the device personality and the updated device personality is determined by: collecting multiple user device personalities; creating statistical distributions to create statistical probabilities to determine how much an individual device personality associated with one user differs from another individual device personality associated with another user; and using the statistical probabilities to determine the set tolerance where a device to which a user has been assigned is statistically different from an other device from another user.
This system operates in the domain of secure transaction authorization, addressing the problem of verifying user identity and device authenticity to prevent unauthorized access. The system uses a device personality—a unique profile derived from user-generated data such as contacts, song names, photo names, and background screen pixel colors—to authenticate transactions. The system includes processors, memory, an input interface, and a transmitter. It receives user information, sends it to a server, and transmits the device personality to the server. When the device personality changes (e.g., due to new contacts or media), the system sends an updated device personality to the server. The server compares the original and updated device personalities, allowing the transaction only if they match within a statistically determined tolerance. The tolerance is set by analyzing multiple user device personalities to create statistical distributions, which quantify how much one user’s device personality differs from another’s. This ensures that the device remains statistically unique to the assigned user, enhancing security. The system dynamically adjusts the tolerance based on real-world data, improving accuracy in distinguishing legitimate users from imposters.
6. The system of claim 5 , where the server comprises two servers.
A system for distributed data processing involves multiple servers working together to handle computational tasks. The system addresses the challenge of efficiently processing large datasets or complex computations by distributing the workload across multiple servers, improving performance and reliability. The system includes at least two servers that collaborate to execute tasks, ensuring redundancy and fault tolerance. Each server is configured to perform specific functions, such as data storage, processing, or communication, to optimize overall system performance. The servers may communicate with each other and with external devices to coordinate tasks, share data, or manage resources. This distributed architecture allows the system to scale dynamically, handling increased workloads by adding more servers as needed. The system may also include mechanisms for load balancing, error detection, and recovery to maintain high availability and efficiency. By leveraging multiple servers, the system enhances processing speed, reduces downtime, and ensures robust data handling.
7. A method for a user to perform a transaction using a first electronic communication device comprising the steps of: connecting with a transaction receiver from the first electronic communication device; receiving at a server a device personality for a second electronic communication device different from the first electronic communication device, the device personality relating to user generated data stored on the second electronic communication device including user contacts, song names, photo names, pixel color of a background screen, or combinations thereof; sending data received from the user on the first electronic communication device to the server; receiving at the server an updated device personality from the second electronic communication device; and comparing the updated device personality and the device personality; performing the transaction only when the updated device personality and the device personality match within a set tolerance, wherein the set tolerance between the device personality and the updated device personality to allow the transaction to proceed is determined by: collecting multiple user device personalities, creating statistical distributions to create statistical probabilities to determine how much an individual device personality associated with one user differs from another individual device personality associated with another user, and using the statistical probabilities to determine the set tolerance where a device to which a user has been assigned is statistically different from an other device from another user storing the updated device personality on the server only when the transaction is approved by the updated device personality and the device personality matching within the set tolerance.
This invention relates to secure transaction authentication using device personality data. The problem addressed is ensuring that a transaction is authorized by the legitimate user of a second electronic communication device, even when the transaction is initiated from a first device. The solution involves analyzing unique user-generated data patterns stored on the second device, such as contacts, song names, photo names, and background screen colors, to create a "device personality" fingerprint. When a transaction is initiated from the first device, the server receives this device personality and later receives an updated version from the second device. The transaction is only approved if the updated personality matches the original within a statistically determined tolerance. This tolerance is calculated by analyzing multiple user device personalities to establish how much variation exists between different users' devices, ensuring that the comparison is both secure and user-specific. The updated personality is only stored on the server if the transaction is approved, maintaining data integrity. This method enhances security by leveraging behavioral and environmental data unique to the user's device, reducing reliance on traditional authentication factors.
8. The method of claim 7 , wherein a comparison of the device personality and the updated device personality is a percent difference.
A system and method for managing device configurations involves comparing a current device personality with an updated device personality to determine configuration changes. The device personality represents the operational state and settings of a device, including hardware and software attributes. The comparison process calculates a percent difference between the current and updated device personalities to quantify the extent of changes. This percent difference provides a measurable metric for assessing configuration modifications, enabling efficient tracking and validation of device updates. The method ensures consistency and accuracy in device management by identifying discrepancies between configurations, allowing for targeted adjustments and maintenance. The system may also include generating alerts or reports based on the comparison results, facilitating proactive management of device configurations. This approach is particularly useful in environments where multiple devices require consistent configuration states, such as in industrial automation, network management, or IoT deployments. The percent difference calculation helps standardize the evaluation of configuration changes, improving reliability and reducing errors in device operations.
9. The method of claim 8 , wherein the set tolerance is between 0.02% and 76% difference.
A system and method for monitoring and controlling the performance of a power generation system, particularly in renewable energy applications such as wind turbines or solar power plants, addresses the challenge of maintaining optimal efficiency and reliability under varying environmental and operational conditions. The system includes sensors for measuring key performance parameters such as power output, temperature, and environmental conditions. A processing unit analyzes these measurements to detect deviations from expected performance levels, which may indicate faults or inefficiencies. The system employs a dynamic tolerance range, set between 0.02% and 76% difference from a baseline or expected value, to determine whether corrective actions are needed. If deviations exceed this tolerance, the system triggers alerts or automatically adjusts operational parameters to restore optimal performance. The method ensures that the power generation system operates within acceptable limits, minimizing downtime and maximizing energy output. The dynamic tolerance allows for flexibility in different operating conditions, ensuring accurate fault detection while avoiding unnecessary interventions. This approach improves the reliability and efficiency of renewable energy systems, reducing maintenance costs and enhancing overall performance.
10. The method of claim 7 , wherein the set tolerance is based on an elapsed time between the receiving of the device personality and the updated device personality of the second electronic communication device at the server.
This invention relates to managing device personalities in a networked system, particularly for updating and synchronizing device configurations across multiple electronic devices. The problem addressed is ensuring reliable and timely updates of device personalities while minimizing unnecessary data transfers and processing overhead. The method involves a server that receives a device personality from a first electronic communication device and an updated device personality from a second electronic communication device. The server determines a set tolerance based on the elapsed time between these two receptions. This tolerance is used to evaluate whether the updated device personality should be applied to the first device. If the elapsed time exceeds the set tolerance, the server may prioritize or conditionally apply the update, ensuring that stale or outdated configurations are not propagated. The method may also involve comparing the received device personalities to detect discrepancies or conflicts, allowing the server to resolve inconsistencies before applying updates. The system ensures that device configurations remain synchronized across the network while accounting for timing constraints, reducing the risk of applying outdated or conflicting updates. This approach is particularly useful in environments where multiple devices may independently modify their configurations, such as in distributed systems or peer-to-peer networks. The method optimizes network efficiency by avoiding unnecessary updates when the elapsed time is within acceptable limits.
11. A system for allowing an authorized transaction, comprising one or more processors, one or more memories, and a communication connection, the one or more memories storing electronic data and instructions, the one or more processors configured to execute the stored instructions and perform the following steps: receive through the communication connection information from a first electronic communication device; receive through the connection from a second electronic communication device, a device personality related to user generated data stored on the second electronic communication device including user contacts, song names, photo names, pixel color of a background screen, or combinations thereof; and permitting the authorized transaction with the first electronic communication device only when a comparison of the device personality and a stored device personality match within a set tolerance; replace the stored device personality with the device personality only when the comparison is within the set tolerance to allow the transaction to proceed, wherein the set tolerance is determined by: collecting multiple user device personalities, creating statistical distributions to create statistical probabilities to determine how much an individual device personality associated with one user differs from another individual device personality associated with another user, and using the statistical probabilities to determine the set tolerance where a device to which a user has been assigned is statistically different from an other device from another user.
This system operates in the domain of secure transaction authorization, addressing the problem of verifying the legitimacy of a user's device to prevent unauthorized access. The system uses a device personality profile, which includes user-generated data such as contacts, song names, photo names, and background screen pixel colors, to authenticate transactions. The system receives information from a first electronic device and a device personality from a second electronic device. It then compares the received device personality with a stored version. If the comparison falls within a predefined tolerance, the transaction is authorized, and the stored device personality is updated. The tolerance is dynamically set by analyzing statistical distributions of multiple user device personalities to determine how much variation exists between different users' devices. This ensures that the system can distinguish between legitimate and fraudulent devices based on statistical differences in user-generated data patterns. The approach enhances security by leveraging unique device usage characteristics rather than traditional authentication methods.
Cooperative Patent Classification codes for this invention. Click any code to explore related patents in that topic.
July 12, 2019
April 12, 2022
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